CN110133725B - Seismic rock transverse wave velocity prediction method and device - Google Patents

Seismic rock transverse wave velocity prediction method and device Download PDF

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CN110133725B
CN110133725B CN201910379349.3A CN201910379349A CN110133725B CN 110133725 B CN110133725 B CN 110133725B CN 201910379349 A CN201910379349 A CN 201910379349A CN 110133725 B CN110133725 B CN 110133725B
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宗兆云
姜曼
印兴耀
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China University of Petroleum East China
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Abstract

The invention discloses a method and a device for predicting seismic rock transverse wave velocity, wherein the method comprises the following steps: acquiring logging data of seismic rocks; determining an equivalent bulk modulus of the rock matrix using an SCA model based on the log data; determining a shear modulus of the rock matrix using the SCA model based on the log data; determining an equivalent bulk modulus of the pore fluid based on the well log data; determining an effective pressure to which the rock matrix is subjected based on the well log data; determining the pore stiffness based on a linear relationship between the effective pressure and a ratio k of the pore stiffness to the equivalent bulk modulus of the rock matrix; determining the equivalent bulk modulus of the saturated rock through a Gassmann fluid replacement model based on the equivalent bulk modulus of the rock matrix, the equivalent bulk modulus of the pore fluid, the pore rigidity and the porosity; based on the equivalent bulk modulus of the saturated rock and the shear modulus of the rock matrix, the compressional and shear wave velocities of the saturated rock are determined. The influence of effective pressure is introduced in modeling, and the accuracy is improved.

Description

Seismic rock transverse wave velocity prediction method and device
Technical Field
The invention relates to the technical field of seismic rock analysis, in particular to a method and a device for predicting the transverse wave velocity of seismic rocks.
Background
The effective pressure is the difference between the confining pressure of the rock and the pore pressure of the rock, and is an important factor influencing the modulus of the rock and the velocity of longitudinal and transverse waves. The rock physical modeling is an important means for seismic rock physical research, and has a guiding function for the research of reservoir characteristics and the exploration and development of oil and gas resources. The rock physical model is an equivalent approximation of complex rocks on the basis of a two-phase medium and equivalent medium theory so as to carry out subsequent rock physical analysis. The accuracy of the rock physical model determines the correctness of the rock physical analysis result, and further influences the accuracy of transverse wave prediction and prestack inversion work.
Experimental research at home and abroad shows that the effective pressure has obvious influence on the modulus and the longitudinal and transverse wave speeds of the rock, and the modulus of the saturated rock is increased along with the increase of the effective pressure. When the effective pressure is lower, the fracture in the rock is closed firstly, so that the modulus and the speed of the rock are increased rapidly, until the effective pressure reaches a critical value, the fracture in the rock is almost completely closed, the effective pressure is increased continuously, the generated influence is no longer obvious, and the elastic modulus and the longitudinal and transverse wave speeds tend to be constant. The influence of the effective stress on the rock modulus and the longitudinal and transverse wave speeds is researched, and the method has important significance for carrying out operations such as transverse wave prediction, formation pressure prediction and the like.
The existing isotropic and anisotropic rock physical modeling method mainly divides rock into rock matrix, rock pores and pore fluid. The modeling process is as follows: 1) averaging the mineral modulus forming the rock matrix to determine the modulus of the rock matrix, such as Voigt-reus-Hill average, Hashin-Shtrikman boundary, and the like; 2) averaging the modulus of the mixed fluid of oil, gas, water and the like by using a Wood formula, a Patch formula and the like to obtain the modulus of the pore fluid; 3) adding pore fluid into the solid rock matrix by using methods such as an SCA model, a DEM model and the like to complete equivalent approximation of the complex rock; 4) and calculating the equivalent modulus, the longitudinal and transverse wave speeds and the like of the rock.
The modeling method does not consider the influence of effective pressure on the rock modulus and the longitudinal and transverse wave speeds, and cannot truly reflect the states of the rock under different effective pressures for reservoirs with relatively developed cracks and higher porosity.
At present, to obtain the change condition of the rock elastic modulus or the longitudinal and transverse wave speeds along with the effective stress, a laboratory measurement method is needed to obtain the change condition, the time consumption is long, the cost is high, and the obtained result application range is smaller. Scholars at home and abroad have already proposed a plurality of empirical formulas for describing the relation between effective stress and longitudinal and transverse wave velocities, but the longitudinal and transverse wave velocities are directly estimated according to empirical rules, the used empirical parameters have quite complicated influence on the longitudinal and transverse wave velocities, and results obtained by different models have great difference and are difficult to apply to actual production.
Disclosure of Invention
The invention aims to provide a method and a device for predicting transverse wave velocity of seismic rock, which are used for solving the technical problem that the influence of effective pressure on rock modulus and longitudinal and transverse wave velocity is not considered in a rock physical modeling method in the prior art.
According to one aspect of the invention, a method for predicting the transverse wave velocity of a seismic rock is provided, which is characterized by comprising the following steps: acquiring logging data of seismic rocks; determining an equivalent bulk modulus K of a rock matrix using an isotropic SCA model based on the well log datam(ii) a Determining shear modulus μ of rock matrix using an isotropic SCA model based on the log datam(ii) a Determining an equivalent bulk modulus K of a pore fluid based on the well log dataf(ii) a Determining an effective pressure P to which the rock matrix is subjected based on the well log datae(ii) a Based on the pore stiffness KφEquivalent bulk modulus K to rock matrixmRatio k to effective pressure PeLinear relationship therebetween, determining the pore stiffness Kφ(ii) a Equivalent bulk modulus K based on rock matrixmEquivalent bulk modulus K of pore fluidfThe pore stiffness KφAnd a porosity phi, determining an equivalent bulk modulus K of the saturated rock by a Gassmann (Gassmann) fluid displacement models(ii) a Based on the equivalent bulk modulus K of the saturated rocksAnd the shear modulus mu of the rock matrixmAnd determining the longitudinal wave velocity and the transverse wave velocity of the saturated rock.
Optionally, the above-mentioned determining the stiffness K of the poresφThe system of equations of (1) is: k is Kφ/KmAnd k is G.PeAnd + I, wherein G is the slope of a work area, I is the intercept, and the values of G and I enable the longitudinal wave velocity error to be minimum.
Optionally, the equivalent bulk modulus K of the saturated rock is determined by the Gassmann fluid replacement model described abovesThe system of equations of (1) is:
Figure BDA0002052819370000021
and
Figure BDA0002052819370000022
alternatively, the above-mentioned determination of the effective pressure P to which the rock matrix is subjectedeThe equation of (a) is: pe＝Pc-PpWherein P iscTo confining pressure, PpIs pore pressure, and Pc＝POB═ g ≈ ρ (z) dz, where POBρ (z) is the density of the rock at depth z from the density log for overburden pressure.
Optionally, the above equivalent bulk modulus K based on said saturated rocksAnd the shear modulus mu of the rock matrixmDetermining the longitudinal wave velocity and the transverse wave velocity of the saturated rock, comprising: based on the equivalent bulk modulus K of the saturated rocksAnd the shear modulus mu of the rock matrixmDetermining the influence of kerogen and layered clay added by using an anisotropic SCA model to obtain a transverse isotropic elastic parameter matrix CSCA(ii) a According to the transverse isotropic elastic parameter matrix CSCADetermining to obtain an equivalent stiffness matrix by adding the influence of vertical soft pores by using an E-C formula
Figure BDA0002052819370000023
Based on the equivalent stiffness matrix
Figure BDA0002052819370000024
And determining the longitudinal wave velocity and the transverse wave velocity of the saturated rock.
According to another aspect of the present invention, there is also provided a seismic rock shear wave velocity prediction apparatus, including: a module for obtaining logging data of seismic rock; determining an equivalent bulk modulus K of a rock matrix using an isotropic SCA model based on the well log datamThe module of (1); method for determining shear modulus μ of rock matrix using isotropic SCA model based on the well log datamThe module of (1); determining an equivalent bulk modulus K of a pore fluid based on the well log datafThe module of (1); for use inDetermining from said log data the effective pressure P to which the rock matrix is subjectedeThe module of (1); for based on pore stiffness KφEquivalent bulk modulus K to rock matrixmRatio k to effective pressure PeLinear relationship therebetween, determining the pore stiffness KφThe module of (1); equivalent bulk modulus K for rock-based matricesmEquivalent bulk modulus K of pore fluidfThe pore stiffness KφAnd porosity phi, determining the equivalent bulk modulus K of the saturated rock by a Gassmann fluid replacement modelsThe module of (1); and, an equivalent bulk modulus K for the saturated rock basedsAnd the shear modulus mu of the rock matrixmAnd a module for determining the longitudinal wave velocity and the transverse wave velocity of the saturated rock.
Optionally, the above-mentioned means for determining the pore stiffness KφEquivalent bulk modulus K to rock matrixmRatio k to effective pressure PeLinear relationship therebetween, determining the pore stiffness KφBy determining the pore stiffness K from the following system of equationsφ：k＝Kφ/KmAnd k is G.PeAnd + I, wherein G is the slope of the work area, I is the intercept, and the values of G and I enable the error between the calculated longitudinal wave speed and the actually measured longitudinal wave speed to be minimum.
Optionally, the equivalent bulk modulus K for rock-based matrices described abovemEquivalent bulk modulus K of pore fluidfThe pore stiffness KφAnd porosity phi, determining the equivalent bulk modulus K of the saturated rock by a Gassmann fluid replacement modelsThe equivalent bulk modulus K of the saturated rock is determined by the following equation systems：
Figure BDA0002052819370000031
And
Figure BDA0002052819370000032
optionally, the above-mentioned means for determining the effective pressure P to which the rock matrix is subjectedeThe effective pressure is determined by the following equationPe：Pe＝Pc-PpWherein P iscTo confining pressure, PpIs pore pressure, and Pc＝POB═ g ≈ ρ (z) dz, where POBρ (z) is the density of the rock at depth z from the density log for overburden pressure.
According to yet another aspect of the present invention, there is also provided a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the seismic rock shear wave velocity prediction method described above when executing the computer program.
The method and the device for predicting the transverse wave velocity of the seismic rock are based on the pore rigidity theory, and the effect of effective pressure on the rock is introduced into rock physical modeling.
Drawings
FIG. 1 is a flow chart of a method for seismic rock shear velocity prediction according to an embodiment of the invention;
FIG. 2 is a block diagram of a seismic rock shear wave velocity prediction apparatus according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a comparison of a calculated compressional velocity and a measured compressional velocity in accordance with an embodiment of the present invention;
FIG. 4 is a schematic diagram of the analysis of the calculated shear wave velocity and the measured value error according to the embodiment of the present invention; and
FIG. 5 is a schematic diagram of a computer device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment provides a rock physical model considering the influence of effective pressure, the influence of the effective pressure on rock modulus is simulated, then the rock longitudinal and transverse wave speeds under different pressures are calculated, and a rock physical modeling method capable of analyzing the rock modulus change conditions under different effective pressures without laboratory measurement and then predicting the transverse wave speed is established.
According to an aspect of an embodiment of the present invention, there is provided a seismic rock shear wave velocity prediction method, as shown in fig. 1, including steps S100 to S114.
And S100, acquiring logging data of seismic rocks.
Step S102, determining an equivalent bulk modulus K of the rock matrix using an isotropic SCA model based on the well log datam. In this example, the equivalent bulk modulus K of the rock matrix can be determined by an isotropic SCA modelm。
In certain examples, the equivalent bulk modulus of the rock matrix is determined from the bulk modulus and the volume content of the various minerals, optionally, in step S102, the equivalent bulk modulus K of the rock matrix is determinedmThe equation of (a) is:
Figure BDA0002052819370000041
wherein, ciIs the volume content of various minerals in the rock matrix, KiIs the bulk modulus of each mineral,
Figure BDA0002052819370000042
is the bulk modulus, P, of the background medium*iIs the geometric factor of the inclusion. Each time a mineral is added to the matrix, the model considers the ith mineral as an inclusion and the other components of the matrix (previously added minerals, etc.) as background media when the ith mineral is added to the matrix.
Step S104, determining the shear modulus mu of the rock matrix by using an isotropic SCA model based on the logging datam。
In some examples, bulk modulus through various mineralsAnd determining the shear modulus of the rock matrix by volume content, optionally in step S104, determining the shear modulus μ of the rock matrixmThe equation of (a) is:
Figure BDA0002052819370000043
wherein, ciIs the volume content of various minerals, muiIs the shear modulus of each mineral,
Figure BDA0002052819370000051
shear modulus, Q, for background media*iIs the geometric factor of the inclusion. Each time a mineral is added to the matrix, the model considers the ith mineral as an inclusion and the other components of the matrix (previously added minerals, etc.) as background media when the ith mineral is added to the matrix.
Step S106, determining the equivalent bulk modulus K of the pore fluid based on the logging dataf. In this example, the shear modulus of the pore fluid is 0.
In certain examples, the equivalent bulk modulus K of the pore fluid is determined in step S104fThe equation of (a) is:
Kf＝SwKw+(1-Sw)Kg；
wherein, KgIs the bulk modulus, K, of the gas in the pore fluidwBulk modulus of water in pore fluid, SwThe water saturation of the pore fluid.
Step S108, determining the effective pressure P to which the rock matrix is subjected based on the logging datae. In this embodiment, the effective pressure P experienced by the rock matrix can be determined from the overburden pressure and pore pressure, taking into account that the confining pressure experienced by the subterranean formation is primarily due to overburden pressuree。
In certain examples, step S108 above determines the effective pressure P to which the rock matrix is subjectedeThe equation of (c) may be:
Pe＝Pc-Pp；
wherein, PcTo confining pressure, PpIs the pore pressure;
in some examples, the confining pressure P may be determined by the following equation, considering that the confining pressure applied to the subterranean formation is mainly due to overburden pressure, and in practical applications, the confining pressure may be estimated by density log datac：
Pc＝POB＝g∫ρ(z)dz；
Wherein, POBρ (z) is the density of the rock at depth z from the density log for overburden pressure.
Step S110, based on the pore stiffness KφEquivalent bulk modulus K to rock matrixmRatio k to effective pressure PeLinear relationship therebetween, determining the pore stiffness Kφ。
In this embodiment, a change in effective pressure changes the stiffness of the pores KφEquivalent bulk modulus K to rock matrixmThe ratio k, k to the effective pressure PeSubstantially linear.
In this embodiment, values of the slope G and the intercept I in different work areas are different, and in practical application, a plurality of groups of values of G and I may be tried with the longitudinal wave velocity as a standard, a group of values of G and I in which an error between the calculated longitudinal wave velocity and the actually measured longitudinal wave velocity is minimized is selected, the ratio K is calculated, and the pore stiffness K is calculatedφ。
In some examples, the pore stiffness K is determined in step S108 aboveφThe system of equations of (1) is:
k＝Kφ/Km，k＝G·Pe+I；
g is work area slope, I is intercept, and G and I take values to make longitudinal wave velocity error minimum.
Step S112, based on the equivalent bulk modulus K of the rock matrixmEquivalent bulk modulus K of pore fluidfThe pore stiffness KφAnd porosity phi, determining the equivalent bulk modulus K of the saturated rock by a Gassmann fluid replacement models。
In the embodiment, the equivalent bulk modulus K of the saturated rock containing the effective pressure influence is obtained through a Gassmann fluid replacement modelsThe influence of effective pressure introduced into the rock physical model is realized.
In some examples, the equivalent bulk modulus K of the saturated rock is determined by the Gassmann fluid replacement model in step S112 abovesThe system of equations of (1) is:
Figure BDA0002052819370000061
step S114, based on the equivalent bulk modulus K of the saturated rocksAnd shear modulus μ of rock matrixmAnd determining the longitudinal wave velocity and the transverse wave velocity of the saturated rock.
In this embodiment, since the effect of the effective pressure on the shear modulus of the rock matrix is insignificant, and therefore the effect of the effective pressure in determining the shear modulus of the rock matrix is negligible, the shear modulus μ of the rock matrix is used in the above step S114mAs the shear modulus of saturated rock.
In some examples, the step S114 is based on the equivalent bulk modulus K of the saturated rocksAnd the shear modulus mu of the rock matrixmAnd determining the longitudinal wave velocity and the transverse wave velocity of the saturated rock, wherein the steps A to C can be included.
Step A, based on the equivalent bulk modulus K of the saturated rocksAnd the shear modulus mu of the rock matrixmDetermining the influence of kerogen and layered clay added by using an anisotropic SCA model to obtain a transverse isotropic elastic parameter matrix CSCA。
In this embodiment, the transversely isotropic elastic parameter matrix C is determined in step ASCAThe equation of (a) is:
Figure BDA0002052819370000062
wherein I is the unit tensor; cnIs the stiffness tensor of the nth component; v isnIs the volume content of isotropic rock and clay particles;
Figure BDA0002052819370000063
is a tensor related to the geometry of the inclusion and can be calculated from the equations of Lin and Mura (1973).
Step B, according to the transverse isotropic elastic parameter matrix CSCADetermining to obtain an equivalent stiffness matrix by adding the influence of vertical soft pores by using an E-C formula
Figure BDA0002052819370000064
In this embodiment, the equivalent stiffness matrix is determined in step B
Figure BDA0002052819370000065
The equation of (a) is:
Figure BDA0002052819370000066
wherein phi iscrackIs the porosity occupied by the soft pores,
Figure BDA0002052819370000067
is a correction term.
Step C, based on the equivalent stiffness matrix
Figure BDA0002052819370000071
And determining the longitudinal wave velocity and the transverse wave velocity of the saturated rock.
In this embodiment, the determining the compressional wave velocity and the shear wave velocity of the saturated rock in step C includes:
step C1: from an equivalent stiffness matrix
Figure BDA0002052819370000072
And (3) calculating:
1) based on the final equivalent stiffness matrix
Figure BDA0002052819370000073
Determining the static bulk modulus Kb of the saturated rock:
Figure BDA0002052819370000074
wherein the content of the first and second substances,
Figure BDA0002052819370000075
Figure BDA0002052819370000076
2) based on the final equivalent stiffness matrix
Figure BDA0002052819370000077
Determining shear modulus of saturated rock in all directions:
G23＝C44；
Figure BDA0002052819370000078
Figure BDA0002052819370000079
G12＝G21；
G13＝G31；
G23＝G32；
wherein, Cij(i, j ═ 1,2,3, …) are elements in the equivalent stiffness matrix.
Step C2: the longitudinal and transverse wave velocities are determined according to the following formula:
Figure BDA00020528193700000710
Figure BDA00020528193700000711
wherein, VPIs the velocity of longitudinal wave, VSIs the transverse wave velocity, C33And C44Is a matrix
Figure BDA00020528193700000712
And rho is the density value obtained by density logging.
And (3) calculating by using logging information with pore pressure data, so that the change conditions of the equivalent volume modulus, the shear modulus and the longitudinal and transverse wave speeds of the rock can be observed when the effective pressure changes.
It should be understood that, although step numbers are labeled in this embodiment, the step numbers do not limit the execution order of the steps in the method, for example, in the embodiment of the present invention, the foregoing step S100 to step S106 may be executed in any order, and details of this embodiment are not repeated.
According to another aspect of the present invention, there is also provided a seismic rock shear wave velocity prediction apparatus 10, as shown in fig. 2, the apparatus 10 comprising: module 100 for acquiring seismic rock well log data for determining the equivalent bulk modulus K of a rock matrix using an isotropic SCA model based on said log datamThe module 101 of (1); for determining the shear modulus mu of a rock matrix based on the well log datamThe module 102 of (1); determining an equivalent bulk modulus K of a pore fluid using an isotropic SCA model based on the well log datafThe module 103 of (a); for determining the effective pressure P to which the rock matrix is subjected based on said well log dataeThe module 104 of (1); for based on pore stiffness KφEquivalent bulk modulus K to rock matrixmRatio k to effective pressure PeLinear relationship therebetween, determining the pore stiffness KφThe module 105 of (a); equivalent bulk modulus K for rock-based matricesmEquivalent bulk modulus K of pore fluidfThe pore stiffness KφAnd porosity phi, determining the equivalent bulk modulus K of the saturated rock by a Gassmann fluid replacement modelsThe module 106 of (1); and, for based on said saturationAnd equivalent bulk modulus K of rocksAnd the shear modulus mu of the rock matrixmA module 107 for determining the compressional and shear wave velocities of the saturated rock.
In some examples, the above-described techniques are used to determine the pore stiffness KφEquivalent bulk modulus K to rock matrixmRatio k to effective pressure PeLinear relationship therebetween, determining the pore stiffness KφModule 105, determining the pore stiffness K by the following system of equationsφ：k＝Kφ/KmAnd k is G.PeAnd + I, wherein G is the slope of a work area, I is the intercept, and the values of G and I enable the longitudinal wave velocity error to be minimum.
In certain examples, the equivalent bulk modulus K for rock-based matrices described abovemEquivalent bulk modulus K of pore fluidfThe pore stiffness KφAnd porosity phi, determining the equivalent bulk modulus K of the saturated rock by a Gassmann fluid replacement modelsModule 106 for determining the equivalent bulk modulus K of said saturated rock by the following system of equationss：
Figure BDA0002052819370000081
And
Figure BDA0002052819370000082
in some examples, the above is used to determine the effective pressure P to which the rock matrix is subjectedeModule 104 for determining the effective pressure P by the following equatione：Pe＝Pc-PpWherein P iscTo confining pressure, PpIs pore pressure, and Pc＝POB═ g ≈ ρ (z) dz, where POBρ (z) is the density log data for overburden pressure.
FIG. 3 is a comparison of calculated compressional-compressional velocities (corresponding to the solid line portion of FIG. 3) and measured compressional-compressional velocities (corresponding to the dashed line portion of FIG. 3) obtained by applying the present petrophysical modeling method to a well at a work area, where V isPIs the velocity of longitudinal wave, VSIs the shear wave velocity.As can be seen from fig. 3, the calculated longitudinal and transverse wave velocities are consistent with the measured longitudinal and transverse wave velocity variation trend, and the numerical difference is small. Further, fig. 4 is a cross wave velocity error distribution histogram, and it can be seen from fig. 4 that the error between the calculated cross wave velocity calculated by the modeling method and the actually measured cross wave velocity is small, and the error requirements of rock physical modeling and shale reservoir cross wave velocity prediction are met.
The embodiment also provides a computer device, such as a smart phone, a tablet computer, a notebook computer, a desktop computer, a rack server, a blade server, a tower server or a rack server (including an independent server or a server cluster composed of a plurality of servers) capable of executing programs, and the like. The computer device 20 of the present embodiment includes at least, but is not limited to: a memory 21, a processor 22, which may be communicatively coupled to each other via a system bus, as shown in FIG. 5. It is noted that fig. 5 only shows a computer device 20 with components 21-22, but it is to be understood that not all shown components are required to be implemented, and that more or fewer components may be implemented instead.
In the present embodiment, the memory 21 (i.e., a readable storage medium) includes a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, and the like. In some embodiments, the storage 21 may be an internal storage unit of the computer device 20, such as a hard disk or a memory of the computer device 20. In other embodiments, the memory 21 may also be an external storage device of the computer device 20, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), or the like, provided on the computer device 20. Of course, the memory 21 may also include both internal and external storage devices of the computer device 20. In this embodiment, the memory 21 is generally used for storing an operating system and various application software installed in the computer device 20, such as the program code of the seismic rock shear wave velocity prediction apparatus 10 in the first embodiment. Further, the memory 21 may also be used to temporarily store various types of data that have been output or are to be output.
Processor 22 may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data Processing chip in some embodiments. The processor 22 is typically used to control the overall operation of the computer device 20. In this embodiment, the processor 22 is configured to execute the program code stored in the memory 21 or process data, for example, execute the seismic rock shear wave velocity prediction apparatus 10, so as to implement the seismic rock shear wave velocity prediction method according to the first embodiment.
The present embodiment also provides a computer-readable storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, a server, an App application mall, etc., on which a computer program is stored, which when executed by a processor implements corresponding functions. The computer readable storage medium of the embodiment is used for storing the device 10 for predicting transverse wave velocity of seismic rock, and when being executed by a processor, the device implements the method for predicting transverse wave velocity of seismic rock of the first embodiment.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.

Claims (10)

1. A method for predicting transverse wave velocity of seismic rocks is characterized by comprising the following steps:
acquiring logging data of seismic rocks;
determining an equivalent bulk modulus K of a rock matrix using an isotropic SCA model based on the well log datam；
Determining shear modulus μ of rock matrix using an isotropic SCA model based on the log datam；
Determining an equivalent bulk modulus K of a pore fluid based on the well log dataf；
Determining an effective pressure P to which the rock matrix is subjected based on the well log datae；
Based on the pore stiffness KφEquivalent bulk modulus K to rock matrixmRatio k to effective pressure PeLinear relationship therebetween, determining the pore stiffness Kφ；
Equivalent bulk modulus K based on rock matrixmEquivalent bulk modulus K of pore fluidfThe pore stiffness KφAnd porosity phi, determining the equivalent bulk modulus K of the saturated rock by a Gassmann fluid replacement models；
Based on the equivalent bulk modulus K of the saturated rocksAnd the shear modulus mu of the rock matrixmAnd determining the longitudinal wave velocity and the transverse wave velocity of the saturated rock.
2. The method of predicting seismic transverse wave velocity of rock of claim 1, wherein the pore stiffness K is determinedφThe system of equations of (1) is: k is Kφ/KmAnd k is G.PeAnd + I, wherein G is a slope, I is an intercept, and the values of G and I minimize an error between the calculated longitudinal wave velocity and the measured longitudinal wave velocity.
3. The method for predicting shear wave velocity of seismic rock according to claim 1, wherein the equivalent bulk modulus K of saturated rock is determined through a Gassmann fluid replacement modelsThe system of equations of (1) is:
Figure FDA0002780137950000011
and
Figure FDA0002780137950000012
4. a method of predicting seismic transverse rock wave velocity according to any one of claims 1 to 3, wherein the effective pressure P to which the rock matrix is subjected is determinedeThe equation of (a) is: pe＝Pc-PpWherein P iscTo confining pressure, PpIs pore pressure, and Pc＝POB═ g ≈ ρ (z) dz, where POBFor overburden pressure, ρ (z) is the formation density value at depth z from the density log and g is the acceleration of gravity.
5. The method of predicting seismic rock shear wave velocity of any one of claims 1 to 3, wherein K is an equivalent bulk modulus of the saturated rocksAnd the shear modulus mu of the rock matrixmDetermining the longitudinal wave velocity and the transverse wave velocity of the saturated rock, comprising:
based on the equivalent bulk modulus K of the saturated rocksAnd the shear modulus mu of the rock matrixmDetermining the influence of kerogen and layered clay added by using an anisotropic SCA model to obtain a transverse isotropic elastic parameter matrix CSCA；
According to the transverse isotropic elastic parameter matrix CSCADetermining to obtain an equivalent stiffness matrix by adding the influence of vertical soft pores by using an E-C formula
Figure FDA0002780137950000021
Based on the equivalent stiffness matrix
Figure FDA0002780137950000022
And determining the longitudinal wave velocity and the transverse wave velocity of the saturated rock.
6. A seismic rock shear wave velocity prediction device, comprising:
a module for obtaining logging data of seismic rocks;
determining an equivalent bulk modulus K of a rock matrix using an isotropic SCA model based on the well log datamThe module of (1);
method for determining shear modulus μ of rock matrix using isotropic SCA model based on the well log datamThe module of (1);
determining an equivalent bulk modulus K of a pore fluid based on the well log datafThe module of (1);
for determining the effective pressure P to which the rock matrix is subjected based on said well log dataeThe module of (1);
for based on pore stiffness KφEquivalent bulk modulus K to rock matrixmRatio k to effective pressure PeLinear relationship therebetween, determining the pore stiffness KφThe module of (1);
equivalent bulk modulus K for rock-based matricesmEquivalent bulk modulus K of pore fluidfThe pore stiffness KφAnd porosity phi, determining the equivalent bulk modulus K of the saturated rock by a Gassmann fluid replacement modelsThe module of (1); and
for equivalent bulk modulus K based on said saturated rocksAnd the shear modulus mu of the rock matrixmAnd a module for determining the longitudinal wave velocity and the transverse wave velocity of the saturated rock.
7. The seismic transverse rock wave velocity prediction device of claim 6, wherein the means for predicting the seismic transverse rock wave velocity is based on the pore stiffness KφEquivalent bulk modulus K to rock matrixmRatio k to effective pressure PeLinear relationship therebetween, determining the pore stiffness KφBy determining the pore stiffness K from the following system of equationsφ：k＝Kφ/KmAnd k is G.Pe+ I, where G is the slope, I is the intercept, and the taking of G and IThe values minimize the error between the calculated longitudinal wave velocity and the measured longitudinal wave velocity.
8. The seismic transverse rock wave velocity prediction device of claim 6, wherein the equivalent bulk modulus K for rock matrix based seismic transverse rock wave velocity prediction devicemEquivalent bulk modulus K of pore fluidfThe pore stiffness KφAnd porosity phi, determining the equivalent bulk modulus K of the saturated rock by a Gassmann fluid replacement modelsThe equivalent bulk modulus K of the saturated rock is determined by the following equation systems：
Figure FDA0002780137950000023
And
Figure FDA0002780137950000024
9. a seismic transverse rock wave velocity prediction apparatus according to any one of claims 6 to 8, wherein the means for determining the effective pressure P to which the rock matrix is subjected based on the log dataeThe effective pressure P is determined by the following equatione：Pe＝Pc-PpWherein P iscTo confining pressure, PpIs pore pressure, and Pc＝POB═ g ≈ ρ (z) dz, where POBFor overburden pressure, ρ (z) is the formation density value at depth z from the density log and g is the acceleration of gravity.
10. A computer arrangement comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the method of any one of claims 1 to 5 when executing the computer program.
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Publication number Priority date Publication date Assignee Title
CN110471129A (en) * 2019-09-20 2019-11-19 西南石油大学 A kind of anisotropic rock Method of Physical Modeling under deep layer shale high temperature and pressure
CN111208566B (en) * 2020-03-04 2021-02-12 中国石油大学(北京) Hole seam parameter inversion method and device based on SCA model and storage medium
CN112505755B (en) * 2020-10-29 2021-11-16 中国石油集团工程咨询有限责任公司 High-precision rock physical modeling method based on self-adaptive mixed skeleton parameters
WO2022198363A1 (en) * 2021-03-22 2022-09-29 中国石油大学(华东) Method and device for predicting elastic parameters of shale reservoir, and storage medium
CN113176614B (en) * 2021-04-30 2022-08-30 中国石油大学(华东) Reservoir effective pressure prestack inversion prediction method based on rock physics theory
CN116559959A (en) * 2023-05-24 2023-08-08 中国石油大学(华东) Deep fracture type reservoir reflection coefficient equation establishment method and related equipment

Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104570129A (en) * 2014-12-19 2015-04-29 中国石油天然气股份有限公司 Method for predicting transversal wave velocity of carbonatite rock reservoir
CN105093332A (en) * 2015-08-24 2015-11-25 中国石油天然气集团公司 Estimating method and estimating apparatus for horizontal wave velocity
CN106324672A (en) * 2015-07-03 2017-01-11 中国石油化工股份有限公司 Petrophysical modeling method and system
CN106368691A (en) * 2015-07-24 2017-02-01 中国石油化工股份有限公司 Method for predicting three-dimensional abnormal pore pressure based on rock physical seismic information
CN106443780A (en) * 2016-08-31 2017-02-22 中国石油集团川庆钻探工程有限公司 Shear wave velocity estimation method for shale gas stratum
CN108008444A (en) * 2017-10-11 2018-05-08 中国石油天然气股份有限公司 A kind of method and device of definite petrophysical model
CN108399270A (en) * 2017-02-08 2018-08-14 中国石油化工股份有限公司 A kind of method of anisotropy shale ratio in determining shale formation
CN109471168A (en) * 2018-11-06 2019-03-15 河海大学 The prediction technique of velocity of longitudinal wave and decaying in a kind of hole fissuted medium
CN109471166A (en) * 2018-12-04 2019-03-15 同济大学 A kind of deep carbonate reservoirs shear wave prediction technique based on porosity type inverting
CN109655940A (en) * 2017-10-12 2019-04-19 中国石油化工股份有限公司 Shale anisotropic rock physical model modeling method
CN109655903A (en) * 2017-10-11 2019-04-19 中国石油化工股份有限公司 Rammell S-Wave Velocity Predicted Method and system

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7299132B2 (en) * 2005-08-08 2007-11-20 Schlumberger Technology Corp. Method and system for pre-drill pore pressure prediction
CN105468886B (en) * 2014-09-04 2018-07-27 中国石油化工股份有限公司 The method for calculating strata pressure based on petrophysical parameters
CN105136621A (en) * 2015-08-18 2015-12-09 昆明理工大学 Analytical method used for simulating reservoir bottom silt with liquid-solid two-phase medium

Patent Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104570129A (en) * 2014-12-19 2015-04-29 中国石油天然气股份有限公司 Method for predicting transversal wave velocity of carbonatite rock reservoir
CN106324672A (en) * 2015-07-03 2017-01-11 中国石油化工股份有限公司 Petrophysical modeling method and system
CN106368691A (en) * 2015-07-24 2017-02-01 中国石油化工股份有限公司 Method for predicting three-dimensional abnormal pore pressure based on rock physical seismic information
CN105093332A (en) * 2015-08-24 2015-11-25 中国石油天然气集团公司 Estimating method and estimating apparatus for horizontal wave velocity
CN106443780A (en) * 2016-08-31 2017-02-22 中国石油集团川庆钻探工程有限公司 Shear wave velocity estimation method for shale gas stratum
CN108399270A (en) * 2017-02-08 2018-08-14 中国石油化工股份有限公司 A kind of method of anisotropy shale ratio in determining shale formation
CN108008444A (en) * 2017-10-11 2018-05-08 中国石油天然气股份有限公司 A kind of method and device of definite petrophysical model
CN109655903A (en) * 2017-10-11 2019-04-19 中国石油化工股份有限公司 Rammell S-Wave Velocity Predicted Method and system
CN109655940A (en) * 2017-10-12 2019-04-19 中国石油化工股份有限公司 Shale anisotropic rock physical model modeling method
CN109471168A (en) * 2018-11-06 2019-03-15 河海大学 The prediction technique of velocity of longitudinal wave and decaying in a kind of hole fissuted medium
CN109471166A (en) * 2018-12-04 2019-03-15 同济大学 A kind of deep carbonate reservoirs shear wave prediction technique based on porosity type inverting

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
predicting S-wave velocities for unconsolidated sediments at low effective pressure;Myung W.Lee;《USGS numbered series：scientific investigations report》;20101231(第2010-5138期);第1-12页 *
上覆压力变化时孔隙岩层弹性波速度的确定及其普遍意义;史謌 等;《中国科学（D辑）》;20011130;第31卷(第11期);第896-901页 *
地震岩石物理学及其应用研究;王炳章;《中国博士学位论文全文数据库 基础科学辑》;20080915(第09(2008)期);第A011-1页 *

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